3.5 Connect: Vibration Condition Monitoring Demo

[MUSIC PLAYNG] Hello, everyone. My name's Adrian Fernandez, and welcome to another episode of Connect. Today, we're bringing in Amit Ashara to talk about a vibration condition monitoring demo where we're going to do things like predictive maintenance by monitoring the vibration of a motor. So really excited to bring you on here, Amit. Do you want to give a quick overview of what we've got in front of us?
Thanks, Adrian. Yes, so what we have in front of us is the MSP432P411 LaunchPad, which is a two megabyte MSP432P4 device which is talking to the CC2650 BoosterPack. And what we have on the top-most board is a three-axis analog accelerometer.
So that's right here? OK.
Yes.
Cool. And then, I guess, working all together, what's happening now?
So right now, what is happening is we have the P411 LaunchPad which is talking to the accelerometer from which it gets three axes of data-- X,Y, and Z.
Cool.
Examples of using the precision ADC that is available on our P4 devices and after data acquisition [? in ?] the 50, it uses the CC26XX device to transmit over Bluetooth.
OK, very cool.
To a wireless device.
OK, awesome. And you guys are doing an FFT on the X, Y, and Z accelerometer data to determine if we're in a good known vibration frequency?
Yes, and also look at the vibration profiles to figure out if there are any internal issues with the motor without having to open the motor.
Awesome. So a person pulls their phone out, and they're able to immediately see if there's something going on?
Yes, indeed.
Awesome. So and that's exactly what we're able to do with this TI application.
Exactly. So, for example, when the green LED comes up, it's basically doing a sampling. So let's look at a very clean waveform. So I connect my app.
And for those that can't see, there is a little motor spinning here underneath this 3D-printed platform. And right now, it's a nice clean signal.
It should be a nice clean signal. So the blue LED is basically showing there is a transfer of data over Bluetooth.
OK, awesome. And right now, you're just downloading all that FFT data coming from the MSP device?
Right. So what I can see is the X, Y, and Z. I can switch off the X, Y or Z, a particular axis of information. I can move between log scale or linear scale. And I can also save the data to my cloud service.
Oh, cool.
The way I want it to.
Awesome.
So as you could see, that we have a very clean waveform, not too much noise. So let's try to introduce noise by actually using this pen and touching it to the motor.
[BUZZING]
So now the sampling is over. I will disconnect, and we will see that it will be a completely different profile.
Gotcha. And we're using, I guess, the high resolution A to D of the MSP device. And this also is capable of high data sampling as well.
Yes, up to one meg of samples a second.
OK, cool.
So as you can see, the waveform has completely shifted. And it has done a significant amount of damage to this pen. So imagine a factory operation, a faulty motor can do some serious human damage.
Absolutely.
Machine damage, cost, liability.
Right, right. There are a lot of things.
And a line-down situation, potentially.
Absolutely, production stop.
Cool. And what we have here is, I guess, the ability to monitor the motor in real time. But if we had a ethernet or Wi-Fi connected gateway we could actually enable remote monitoring of the motors.
Yes. You could use machine learning on a cloud service to be able to plot expected time of failure.
Gotcha. Very cool. Awesome, well thanks so much, Amit. This is a really cool demo. I can definitely see how this is key in an industrial setting. Do you know how developers can get started with this particular set up?
Yes, so they can use the TI design number, TIDA on TI website.
OK, cool.
Or they can go to ti.com and type in vibration condition monitoring to get access to the resources they require.
Very cool. Thanks for hanging out, Amit. Very cool demo. Be sure to check out the TI design that Amit talked about here to get started with your own motor fault monitoring system.
You can also tune in next week. We'll learn more about new simple link platform products. Additionally, get started with some of these applications that are available on the TI Design Network.
[MUSIC PLAYING]
Thanks.

Details

Date:
September 17, 2018

In this episode, Amit will showcase an example of predictive maintenance, called vibration condition monitoring, using the SimpleLink MSP432p4111 MCU and the CC26x2 Bluetooth low energy wireless MCU (SoC). The ability to predict the life of a motor gives an operator the ability to optimize maintenance schedules of often costly and large motors/pumps while improving the operational lifetime of the production lines using these motors, often without any lapse in production.